“All Is Fair in… Meme!” How Heterosexual Users Perceive and React to Memes, News, and Posts Discriminating against Sexual Minorities

Datos Bibliográficos

ID17820144
AutoresChiara Imperato (0000-0002-4787-0631, University of Parma, autor de correspondencia), Maria Pagano (0000-0001-6826-0480, University of Bologna), Tiziana Mancini (0000-0001-7173-6478, University of Parma)
Año2023
Volumen12
Número2
Páginas74-74
Fecha de publicación2023-01-31
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSocial Sciences (JOURNAL)
Identificadores de la revistaISSN: 2076-0760 • E-ISSN: 2076-0760
EditorialMDPI AG (PUBLISHER • IT)
DOI10.3390/socsci12020074
OpenAlexW4318612201
IdiomaEN
Citas recibidas5
Referencias citadas18

Digital discrimination against sexual minorities is becoming prevalent. It increasingly spreads through discriminatory content that mixes text and images (e.g., memes), thus, making online discrimination more difficult to detect. The present survey study focused on digital content that is discriminatory towards sexual minorities, aiming to analyze whether a sample of heterosexual social network users (65.2% female; Mage = 27.13) perceived different forms of discriminatory content (i.e., memes, news, and posts) as equally offensive and to what extent such different forms elicited the same online behavioral reactions. Furthermore, we considered how individuals’ online network heterogeneity could influence their perception of digital discrimination. Results showed that individuals perceived memes as less offensive when compared to both news and posts. Accordingly, we also found that individuals took less time to react to posts when compared to the other forms of content. In addition, those who declared that they had a heterogenous online network perceived memes as more offensive than those who did not. Finally, regarding reacting behaviors, overall results showed that memes elicited few proactive behaviors and more acquiescent and ignoring behaviors than news and posts. The theoretical and practical implications of these results are discussed

Digital content · Multimedia · Offensive · Perception · Computer Science · Gender, Feminism, and Media · Hate Speech and Cyberbullying Detection · Psychology · Social Media and Politics · Social Psychology